Assessment of the impacts of constructing artificial structures on the water quality and hydrological environment of a meandering river.

When an artificial structure is built in a river, the river changes significantly in water quality and hydraulic properties. In this study, the effects of the weirs constructed in the middle section of a river as a four major rivers restoration project in Korea on water quality and hydrological characteristics were analyzed. For multi-dimensional data analysis, a self-organizing map was applied, and statistical techniques including analysis of variation were used. As a result of analysis, the cross-sectional area of the river increased significantly after the construction of the weir compared to before the construction of the weir, and the flow velocity decreased at a statistically significant level. In the case of water quality, nitrogen, phosphorus, and suspended solids tended to improve after weir construction, and chlorophyll-a and bacteria tended to deteriorate. Some water quality parameters such as chlorophyll-a were also affected by seasonal influences. In order to improve the water quality deteriorated by the construction of the weir, it is necessary to consider how to improve the flow velocity of the river through partial opening or operation of the weir. In addition, in order to determine the effect of sedimentation of particulate matter due to the decrease in flow rate, it is necessary to conduct investigations on sediments around weirs in the future. PRACTITIONER POINTS: Compared to before the construction of the weir, there was no significant change in the flow rate of the river after the construction of the weir. In the case of chlorophyll-a and bacteria, the water quality was deteriorated after weir construction. To improve the deteriorated water quality, it is required to consider the fundamental management of each pollutant source and the flexible operation of both weirs. For some improved water quality parameters, further research is needed to determine whether these improvements are directly attributable to the construction of a weir.

Advanced hydrological streamflow simulation in a watershed using adjusted radar-rainfall estimates as meteorological input data.

Among the input data of the watershed model for simulating changes of flowrate in the watershed, weather input data, especially input data related to rainfall, are the most important. Therefore, it is important to ensure the accuracy of rainfall input data to increase the accuracy of the watershed model results. Securing rainfall measurements with finer spatial and temporal resolutions is important in predicting flowrate variations at a sub-catchment, especially as they relate to global and local climate changes in weather conditions such as rainfall depth, rainfall intensity, etc. In this study, adjusted radar-rainfall estimates were suggested as alternative input data for watershed modeling. Through a statistical analysis of the representativeness of a ground rainfall measurement (10 km × 10 km grid), the necessity of radar-rainfall estimates (2 km × 2 km grid) was identified. By applying calibration factors to initial radar-rainfall estimates and comparing adjusted radar-rainfall estimates with ground rainfall measurements, it was proven that adjusted radar-rainfall estimates could be used as input data for watershed simulations (NSE > 0.92; n = 12). Adjusted radar-rainfall estimates and ground rainfall measurements were used as input data of the Soil and Water Assessment Tool model to predict flowrate variations at the outlets of a tributary and the entire watershed. As a result, the accuracies of the simulation results were improved for the outlets of a tributary and the entire watershed (NSE: 0.33 to 0.48 and 0.19 to 0.55, respectively). To obtain more reliable rainfall data, radar images easily accessible to users were applied, and the accuracy of the data was increased by applying simple equations to numerical data extracted from radar image processing. Additionally, the applicability of the adjusted radar-rainfall estimates was demonstrated by comparing the modeling results using the suggested rainfall data and existing ground-based rainfall data. The suggested methodologies are expected to contribute to more accurately predict the possibility of flood disasters in other regions and countries lacking infrastructure related to rainfall measurements and to establish appropriate countermeasures.

Achieving a High Areal Capacity with a Binder-Free Copper Molybdate Nanocone Array-Based Positive Electrode for Hybrid Supercapacitors.

Herein, we develop a binder-free copper molybdate nanocone array with a prism-like morphology on nickel foam (Cu3Mo2O9 NCAs/Ni foam) using a single-step hydrothermal method. With an optimal growth time (10 h) under hydrothermal conditions, the prism-like Cu3Mo2O9 NCAs are uniformly decorated on Ni foam with good adhesion and crystallinity. The prepared Cu3Mo2O9 NCAs/Ni foam has been directly used as a binder-free electrode to examine its suitability as a positive electrode in hybrid supercapacitors. In an aqueous 1 M KOH electrolyte, the binder-free Cu3Mo2O9 NCAs/Ni foam showed battery-type behavior with a high areal capacity of 449.5 µAh cm-2 at a discharge current density of 2 mA cm-2 and also exhibited a good cycling stability. In addition, the pouch-type hybrid supercapacitor is assembled using the prism-like Cu3Mo2O9 NCAs/Ni foam as a positive electrode and the activated carbon as a negative electrode in a 1 M KOH electrolyte. The hybrid supercapacitor achieves a maximum cell potential of 1.6 V with superior energy storage properties, including a high areal capacitance of 609.7 mF cm-2 at 3.5 mA cm-2, a high areal energy (0.21 mWh cm-2), and a high power density (2.73 mW cm-2). The obtained results suggest that the facilely synthesized Cu3Mo2O9 NCAs/Ni foam electrode has great potential in high-performance energy storage devices.

Fallen leaves derived honeycomb-like porous carbon as a metal-free and low-cost counter electrode for dye-sensitized solar cells with excellent tri-iodide reduction.

Utilizing carbon-based counter electrodes (CEs) in dye-sensitized solar cells (DSSCs) have received much attention in recent times, owing to their low cost, good electrochemical activity, natural abundance and eco-friendly nature. Herein, we have facilely prepared quince leaves derived porous carbon (QLPC) using fallen quince leaves (QLs) and it was used as a cost-effective CE for the fabrication of DSSCs. By means of alkali treatment and pyrolysis process (at different temperatures of 700, 800 and 900 °C), the QLs powder undergoes chemical activation and carbonization, which results in a honeycomb-like QLPC with abundant micro/mesopores and large surface area. Simple and straightforward coating of QLPC samples onto fluorine doped tin oxide glass substrates led to improved electrocatalytic activity and good tri-iodide reduction in DSSCs. When the DSSCs were illuminated under 1 sun condition (AM 1.5; 100 mW cm-2), the device assembled with QLPC-based CE (prepared at 800 °C) showed a higher current density of ∼14.99 mA/cm2 and power conversion efficiency of ∼5.52% among the other QLPC-based CEs, which are comparable with the platinum-based CE in DSSCs. This facile process for the preparation of biomass derived carbon-based CE provides an alternative to the noble metal-free CE in DSSCs.

Ultrathin nickel hydroxide nanosheet arrays grafted biomass-derived honeycomb-like porous carbon with improved electrochemical performance as a supercapacitive material.

Three-dimensional hierarchical honeycomb-like activated porous carbon pillared ultrathin Ni(OH)2 nanosheets (Ni(OH)2 NSs@HAPC) for use as supercapacitor materials were facilely synthesized. With an aid of pine cone flowers as a biomass source, HAPC conducting scaffolds were prepared by the alkali treatment and pyrolysis methods under an inert gas atmosphere. Subsequently, the Ni(OH)2 NSs were synthesized evenly on the surface of HAPC via a solvothermal method. The resulting HAPC and Ni(OH)2 NSs@HAPC composite materials offered free pathways for effective diffusion of electrolyte ions and fast transportation of electrons when employed as an electrode material. The Ni(OH)2 NSs@HAPC composite electrode exhibited excellent electrochemical properties including a relatively high specific capacitance (Csp) value of ~ 916.4 F/g at 1 A/g with good cycling stability compared to the pristine HAPC and Ni(OH)2 NSs electrodes. Such bio-friendly derived carbon-based materials with transition metal hydroxide/oxide composite materials could be a promising approach for high-performance energy storage devices because of their advantageous properties of cost effectiveness and easy availability.

Birnessite-type MnO2 nanosheet arrays with interwoven arrangements on vapor grown carbon fibers as hybrid nanocomposites for pseudocapacitors.

Manganese dioxide nanosheet arrays with interconnected arrangements are easily synthesized on vapor grown carbon fibers (MnO2 NSAs@VCFs) by a simple wet-chemical method at low temperature. The conductive nature of the VCFs serves as a scaffold and easily reduces potassium permanganate species for the formation of hierarchical MnO2 NSAs@VCFs. When utilized as an electroactive material for pseudocapacitors, the sophisticated configuration of the nanocomposite provides an effective electrochemical activity and an electron pathway for higher electrochemical performance in 1 M Na2SO4 aqueous solution. The hierarchical MnO2 NSAs@VCFs exhibit a maximum specific capacitance of 115.3 F g-1 at a current density of 0.5 A g-1 with an excellent cycling stability of 85.6% after 2000 cycles at a current density of 5 A g-1. Such facile and cost-effective fabrication of a metal oxide nanocomposite with improved electrochemical performance allows it to be considered as a promising electroactive material for energy storage devices.

Enhanced Photovoltaic Performance of Dye-Sensitized Solar Cells by Efficient Near-Infrared Sunlight Harvesting using Upconverting Y2O 3:Er (3+)/Yb (3+) Phosphor Nanoparticles.

We report the efficiency enhancement in dye-sensitized solar cells (DSSCs) using Er(3+)/Yb(3+)-co-doped Y2O3 (i.e., Y2O3:Er(3+)/Yb(3+)) phosphor nanoparticles, prepared by a simple and cost-effective urea-based homogeneous precipitation method, for efficient near-infrared (NIR) sunlight harvesting. Under the light excitation at a wavelength of 980 nm, the as-prepared samples exhibited strong upconversion emissions at green and red visible wavelengths. To investigate the influence of Y2O3:Er(3+)/Yb(3+) nanoparticles on the photovoltaic performance of DSSCs, the phosphor nanoparticles were incorporated into titanium dioxide films to form a composite photoelectrode. For the resulting DSSCs, the increased power conversion efficiency (PCE) of 6.68 % was obtained mainly by the increased photocurrent of J SC = 13.68 mA/cm(2) due to the light harvesting enhancement via the NIR-to-visible upconversion process (cf., PCE = 5.94 %, J SC = 12.74 mA/cm(2) for the reference DSSCs without phosphor nanoparticles), thus, indicating the PCE increment ratio of ~12.4 %.

Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea.

Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vector machine (SVM) were used to predict Chl-a concentration for the early warning in the Juam Reservoir and Yeongsan Reservoir, which are located in an upstream region (freshwater reservoir) and downstream region (estuarine reservoir), respectively. Weekly water quality data and meteorological data for a 7-year period were used to train and validate both the ANN and SVM models. The Latin-hypercube one-factor-at-a-time (LH-OAT) method and a pattern search algorithm were applied to perform sensitivity analyses for the input variables and to optimize the parameters of the two models, respectively. Results revealed that the two models well-reproduced the temporal variation of Chl-a based on the weekly input variables. In particular, the SVM model showed better performance than the ANN model, displaying a higher prediction accuracy in the validation step. The Williams-Kloot test and sensitivity analysis demonstrated that the SVM model was superior for predicting Chl-a in terms of prediction accuracy and description of the cause-and-effect relationship between Chl-a concentration and environmental variables in both the Juam Reservoir and Yeongsan Reservoir. Furthermore, a 7-day interval was determined as an efficient early warning interval in the two reservoirs. As such, this study suggested an effective early-warning prediction method for Chl-a concentration and improved the eutrophication management scheme for reservoirs.

Evaluation of the relationship between two different methods for enumeration fecal indicator bacteria: colony-forming unit and most probable number.

Most probable number (MPN) and colony-forming unit (CFU) estimates of fecal indicator bacteria (FIB) concentration are common measures of water quality in aquatic environments. Thus, FIB intensively monitored in Yeongsan Watershed in an attempt to compare two different methods and to develop a statistical model to convert from CFU to MPN estimates or vice versa. As a result, the significant difference was found in the MPN and CFU estimates. The enumerated Escherichia coli concentrations in MPN are greater than those in CFU, except for the measurement in winter. Especially in fall, E. coli concentrations in MPN are one order of magnitude greater than that in CFU. Contrarily, enterococci bacteria in MPN are lower than those in CFU. However, in general, a strongly positive relationship are found between MPN and CFU estimates. Therefore, the statistical models were developed, and showed the reasonable converting FIB concentrations from CFU estimates to MPN estimates. We expect this study will provide preliminary information towards future research on whether different analysis methods may result in different water quality standard violation frequencies for the same water sample.

Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin.

This study reveals land-use factors that explain stream water quality during wet and dry weather conditions in a large river basin using two different linear models-multiple linear regression (MLR) models and constrained least squares (CLS) models. Six land-use types and three topographical parameters (size, slope, and permeability) of the watershed were incorporated into the models as explanatory variables. The suggested models were then demonstrated using a digitized elevation map in conjunction with the land-use and the measured concentration data for Escherichia coli (EC), Enterococci bacteria (ENT), and six heavy metal species collected monthly during 2007-2008 at 50 monitoring sites in the Yeongsan Watershed, Korea. The results showed that the MLR models can be a powerful tool for predicting the average concentrations of pollutants in stream water (the Nash-Sutcliffe (NS) model efficiency coefficients ranged from 0.67 to 0.95). On the other hand, the CLS models, with moderately good prediction performance (the NS coefficients ranged 0.28-0.85), were more suitable for quantifying contributions of respective land-uses to the stream water quality. The CLS models suggested that industrial and urban land-uses are major contributors to the stream concentrations of EC and ENT, whereas agricultural, industrial, and mining areas were significant sources of many heavy metal species. In addition, the slope, size, and permeability of the watershed were found to be important factors determining the extent of the contribution from each land-use type to the stream water quality. The models proposed in this paper can be considered useful tools for developing land cover guidelines and for prioritizing locations for implementing management practices to maintain stream water quality standard in a large river basin.

Spatial and temporal variability of fecal indicator bacteria in an urban stream under different meteorological regimes.

As a representative urban stream in Korea, the Gwangju (GJ) stream suffers from chronic fecal contamination. In this study, to characterize levels of fecal pollution in the GJ stream, the monthly monitoring data for seven years (from 2001 to 2007) and the hourly monitoring data from two field experiments were examined with respect to seasonal/daily variations and spatial distribution under wet and dry weather conditions. This research revealed that concentrations of fecal indicator bacteria strongly varied depending on the prevalent meteorological conditions. That is, during the dry daytime, fecal indicator bacteria concentrations decreased due to inactivation from solar irradiation, but rapidly increased in the absence of sunlight, suggesting external source inputs. In addition, bacterial concentrations substantially increased during rainfall events, due probably to a major contribution from combined sewer overflow. The observations in this study can be useful for implementing fecal pollution management strategies and for predicting fecal contamination as a function of meteorological conditions.

Meteorological effects on the levels of fecal indicator bacteria in an urban stream: a modeling approach.

Gwangju Creek (GJC) in Korea, which drains a highly urbanized watershed, has suffered from substantial fecal contamination, thereby limiting the beneficial use of the water in addition to threatening public health. In this study, to quantitatively estimate the sinks and sources of fecal indicator bacteria (FIB) in GJC under varying meteorological conditions, two FIB (i.e., Escherichia coli and enterococci bacteria) were monitored hourly for 24h periods during both wet and dry weather conditions at four sites along GJC, and the collected data was subsequently used to develop a spatiotemporal FIB prediction model. The monitoring data revealed that storm washoff and irradiational die-off by sunlight are the two key processes controlling FIB populations in wet and dry weather, respectively. FIB populations significantly increased during precipitation, with greater concentrations occurring at higher rainfall intensity. During dry weather, FIB populations decreased in the presence of sunlight in daytime but quickly recovered at nighttime due to continuous point-source inputs. In this way, the contributions of the key processes (i.e., irradiational die-off by sunlight, settling, storm washoff, and resuspension) to the FIB levels in GJC under different meteorological conditions were quantitatively estimated using the developed model. The modeling results showed that the die-off by sunlight is the major sink of FIB during the daytime in dry weather with a minor contribution from the settling process. During wet weather, storm washoff and resuspension are equally important processes that are responsible for the substantial increase of FIB populations.

Factors dominating stratification cycle and seasonal water quality variation in a Korean estuarine reservoir.

A comprehensive monitoring program was conducted during 2005-2007 to investigate seasonal variations of hydrologic stability and water quality in the Yeongsan Reservoir (YSR), located at the downstream end of the Yeongsan River, Korea. A principal component analysis (PCA) was performed to identify factors dominating the seasonal water quality variation from a large suite of measured data--11 physico-chemical parameters from 48 sampling sites. The results showed that three principal components explained approximately 62% of spatio-seasonal water quality variation, which are related to stratifications, pollutant loadings and resultant eutrophication, and the advective mixing process during the episodic rainfall-runoff events. A comparison was then made between YSR and an upstream freshwater reservoir (Damyang Reservoir, DYR) in the same river basin during an autumn season. It was found that the saline stratification and pollutant input from the upstream contributed to greater concentrations of nutrients and organic matter in YSR compared to DYR. In YSR, saline stratification in combination with thermal stratification was a dominant cause of the longer period (for two consecutive seasons) of hypoxic conditions at the reservoir bottom. The results presented here will help better understand the season- and geography-dependent characteristics of reservoir water quality in Asian Monsoon climate regions such as Korea.

Factors affecting metal exchange between sediment and water in an estuarine reservoir: a spatial and seasonal observation.

Water quality response in a reservoir has often been assessed using relatively restricted datasets that cannot provide sufficient information, thereby giving rise to a dramatic over- or underestimate of actual figures. In this paper we discuss how the levels of metallic elements between the sediment and overlying water in an estuarine reservoir can be influenced by aquatic parameters in response to spatial and seasonal conditions. To better elucidate the interfacial exchange between sediment and water, statistical analyses are employed to intensive data sets collected from the Yeongsan Reservoir (YSR), Korea, which has undergone widespread deterioration in water quality due to the continuous growth of anthropogenic sources. During three seasonal sampling campaigns, we found that oxygen deficiency at the bottom water layer promotes Fe and Ni accumulation in sediment, likely due to the formation of sulfide and oxide complexes under anoxic and suboxic environments, respectively. In addition, salinity levels as high as 11 per thousand in the bottom water layer during autumn substantially increase the release of Mn, restricting the use of YSR as a primary source of agricultural irrigation water. Although most dissolved metals are at acceptable levels for sustaining aquatic life, it is recommended that for long-term planning the elevated Fe and Mn levels in sediment should be controlled with oxygen deficiency during dry weather to ensure a sustainable water supply or, at a minimum, better coordinated operation of YSR.

Decadal and seasonal scale changes of an artificial lake environment after blocking tidal flows in the Yeongsan Estuary region, Korea.

Artificial lakes, initially built in estuaries for positive purposes such as flood prevention and providing irrigation water, have been found to have negative impacts including blocking tidal cycles, disappearance of brackish water zones, sediment increase, water pollution, change of microbial diversity inhabiting patterns, and a decline in fish diversity. In this study, multidisciplinary field studies including physical, chemical, and biological analyses were performed to demonstrate decadal and seasonal scale changes in the ecological environment in Yeongsan Reservoir (YSR), Korea, since the construction of a 4.35 km-long dam in 1981. The results of the study show that the volume of sediment accumulated in YSR was 75.2 million m(3) since the dam was constructed, resulting in a 33.6% reduction of the total water storage capacity. Also, water quality in YSR was affected by complex physico-chemical and hydrological phenomena, including saline and thermal stratifications, and pollutant loadings leading to eutrophication. Subsequent sediment bacteria analyses showed microbial diversity according to different depths in sediment, indicating the environmental change of sediment ecology. Moreover, the fish diversity in this study (2006-2007) was found to be considerably reduced compared to a similar study in 1989 (42% reduction), and the ecological health was deemed to be in a "poor" condition based on the 10-metric Lentic Ecosystem Health Assessment (LEHA) model. Accordingly, these results indicate that aquatic ecosystems are detrimentally affected by estuarine dams that block tidal flows, and when applied to short/long-term management strategies for artificial lakes in estuaries, suggest that similar construction projects have to be suitably controlled.

Effect of environmental flow management on river water quality: a case study at Yeongsan River, Korea.

This paper describes a management scheme to control river water quality using additional water discharges from upstream dams, which results in an increase environmental flow (EF) followed by an enhancement of water quality in a target river. To suggest a creditable management plan among a suite of ideal scenarios, the monthly averaged water quality monitoring data from 2001 to 2006 at the Yeongsan (YS) River, Korea were investigated with respect to seasonal variation and spatial distribution. From the analysis, it was found that while biochemical oxygen demand (BOD(5)) level in the YS River was extremely high during the dry/drought season (April, May, and June; AMJ), the level was subsequently decreased during the monsoon season (July, August, and September; JAS) due mainly to the dilution effect of rainfall. To improve the water quality in AMJ, we here suggested a scenario of increasing EF using surplus water discharges from upstream dams, which was examined by one dimensional riverine water quality model, QUAL2E model. Simulation result showed that additional discharge from the upstream dams could lead, on average, to a 36% of water quality improvement in mainstream with respect to BOD(5). Model coefficients were validated by comparing the six year monitoring data to minimize a sum of squares error, and showed a good agreement with the observed data. Overall, the methodology developed in this paper appears to be quite clear and straightforward, and thus, can be applied to a wide range of the flow managements or water quality controls in a stream with artificial structures.

Evaluation of pollutants removal efficiency to achieve successful urban river restoration.

Greater efforts to provide alternative scenarios are key to successful urban stream restoration planning. In this study, we discuss two different aspects of water quality management schemes, biodegradation and human health, which are incorporated in the restoration project of original, pristine condition of urban stream at the Gwangju (GJ) Stream, Korea. For this study, monthly monitoring of biochemical oxygen demand (BOD(5)) and fecal indicator bacteria (FIB) data were obtained from 2003 to 2008 and for 2008, respectively, and these were evaluated to explore pollutant magnitude and variation with respect to space and time window. Ideal scenarios to reduce target pollutants were determined based on their seasonal characteristics and correlations between the concentrations at a water intake and discharge point, where we suggested an increase of environmental flow and wetland as pollutants reduction drawing for BOD(5) and FIB, respectively. The scenarios were separately examined by the Qual2E model and hypothetically (but planned) constructed wetland, respectively. The results revealed that while controlling of the water quality at the intake point guaranteed the lower pollution level of BOD(5) in the GJ Stream, a wetland constructed at the discharge point may be a promising strategy to mitigate mass loads of FIB. Overall, this study suggests that a combination of the two can be plausible scenarios not only to support sustainable urban water resources management, but to enhance a quality of urban stream restoration assignment.

A new methodology for determining dispersion coefficient using ordinary and partial differential transport equations.

The present study proposes a methodology for determining the effective dispersion coefficient based on the field measurements performed in Gwangju (GJ) Creek in South Korea which is environmentally degraded by the artificial interferences such as weirs and culverts. Many previous works determining the dispersion coefficient were limited in application due to the complexity and artificial interferences in natural stream. Therefore, the sequential combination of N-Tank-In-Series (NTIS) model and Advection-Dispersion-Reaction (ADR) model was proposed for evaluating dispersion process in complex stream channel in this study. The series of water quality data were intensively monitored in the field to determine the effective dispersion coefficient of E. coli in rainy day. As a result, the suggested methodology reasonably estimates the dispersion coefficient for GJ Creek with 1.25 m(2)/s. Also, the sequential combined method provided Number of tank-Velocity-Dispersion coefficient (NVD) curves for convenient evaluation of dispersion coefficient of other rivers or streams. Comparing the previous studies, the present methodology is quite general and simple for determining the effective dispersion coefficients which are applicable for other rivers and streams.

Characteristics of wet and dry weather heavy metal discharges in the Yeongsan Watershed, Korea.

A comprehensive water quality monitoring program was conducted in the Yeongsan (YS) River, Korea from 2005 to present to investigate wet and dry weather pollutant discharge in an attempt to establish point and non-point pollution management strategies. As part of this monitoring program, 11 heavy metal species were measured during dry and wet weather conditions in the YS River, where Gwangju City (GJ), a subcatchment of the YS River, was further monitored to clarify the responsibility of different metal species discharged into the mainstream. Monthly grab water samples showed that greater amounts of metals along the YS River were discharged during the wet summer months due largely to storm runoff. In addition, further monitoring results revealed that GJ, a highly urbanized area, was a significant contributor of the heavy metals being discharged into the YS River during both wet and dry weather. The most abundant metal species discharged from GJ were manganese, aluminum and iron with different contributions of wet and dry weather flows to the total discharge load. Wet weather flow was a significant contributor to the annual dissolved metal loads, accounting for 44-93% of the annual load depending on the metal species, with the exception of chromium and cadmium (9% and 27%, respectively). Mostly, metal loads during wet weather were shown to be proportional to the rainfall depth and antecedent dry period. A substantial fraction of metals were also associated with solids, suggesting that sedimentation might be an appropriate management practice for reducing the metal load generated in GJ. Overall, although dissolved metal concentrations in YS River were at an acceptable level for aquatic community protection, continual metal discharge throughout the year was considered to be a potential problem in the long-term due to gradual water quality degradation as well as continuous metal accumulation in the system.

Determination of the optimal parameters in regression models for the prediction of chlorophyll-a: a case study of the Yeongsan Reservoir, Korea.

Statistical regression models involve linear equations, which often lead to significant prediction errors due to poor statistical stability and accuracy. This concern arises from multicollinearity in the models, which may drastically affect model performance in terms of a trade-off scenario for effective water resource management logistics. In this paper, we propose a new methodology for improving the statistical stability and accuracy of regression models, and then show how to cope with pitfalls in the models and determine optimal parameters with a decreased number of predictive variables. Here, a comparison of the predictive performance was made using four types of multiple linear regression (MLR) and principal component regression (PCR) models in the prediction of chlorophyll-a (chl-a) concentration in the Yeongsan (YS) Reservoir, Korea, an estuarine reservoir that historically suffers from high levels of nutrient input. During a 3-year water quality monitoring period, results showed that PCRs could be a compact solution for improving the accuracy of the models, as in each case MLR could not accurately produce reliable predictions due to a persistent collinearity problem. Furthermore, based on R(2) (goodness of fit) and F-overall number (confidence of regression), and the number of explanatory variables (R-F-N) curve, it was revealed that PCR-F(7) was the best model among the four regression models in predicting chl-a, having the fewest explanatory variables (seven) and the lowest uncertainty. Seven PCs were identified as significant variables, related to eight water quality parameters: pH, 5-day biochemical oxygen demand, total coliform, fecal indicator bacteria, chemical oxygen demand, ammonia-nitrogen, total nitrogen, and dissolved oxygen. Overall, the results not only demonstrated that the models employed successfully simulated chl-a in a reservoir in both the test and validation periods, but also suggested that the optimal parameters should cautiously be considered in the design of regression models.